DESCRIPTION: This multi-center prospective cohort study will: (i) Determine baseline prevalence rates and subsequent incidence rates over a 2 year period for low back pain (LBP), LBP with neurological signs (sciatica), LBP-related impairments, lost time and modified duty-related LBP for 3 levels of job physical exposures (low, medium, high), (ii) Quantify job and individual risk factors (e.g., weights, frequency, horizontal and vertical locations, low back moments, etc.), (iii) Validate existing job analysis methods (especially Revised NIOSH Lifting Equation, Maximum Acceptable Weights land Forces, 3-D Static Strength Biomechanical Model, the Proposed TLV for Lifting, and the Washington State Checklist, and (iv) Develop a final model for determining MSD risks. A cohort of 678 workers (study drop-outs replaced) from 10 very different industries with a total worker population of over 10,000 in three diverse states will ;) participate in the study to help ensure generalizability of the study results. To maximize objectivity and accuracy, job physical exposures will rely primarily on measurements to quantify exposures. To maximize clinical and epidemiological validity and reliability, all participants will have health outcomes assessments by Physical Therapists and qualified physicians. These will include: baseline questionnaires, structured interviews and standardized physical examinations. Changes in job physical exposures will be monitored monthly. LBP symptoms, sciatica, LBP impairments and LBP severity measures will be assessed monthly using a symptom questionnaire on all, and structured interviews/physical examinations on those with symptoms. Job physical exposure and health outcomes assessment teams will be blinded to each other throughout the field observation phase. Multivariate logistic regression models and survival analyses will be utilized to explore relationships between job physical risk factors and low back pain (LBP), sciatica, LBP impairments and LBP severity measures. In addition to quantifying ergonomic risk factors, interactions between various jobs, psychosocial and individual risk factors will be explored. This project is expected to result in the ability to improve the existing ergonomic job evaluation models that have robust predictive capabilities for a broad range of industries.